final def==(arg0: AnyRef): Boolean

final def==(arg0: Any): Boolean

Aggregate the elements of each partition, and then the results for all the partitions, using
given combine functions and a neutral "zero value".

Aggregate the elements of each partition, and then the results for all the partitions, using
given combine functions and a neutral "zero value". This function can return a different result
type, U, than the type of this RDD, T. Thus, we need one operation for merging a T into an U
and one operation for merging two U's, as in scala.TraversableOnce. Both of these functions are
allowed to modify and return their first argument instead of creating a new U to avoid memory
allocation.

defcheckpoint(): Unit

Mark this RDD for checkpointing.

Mark this RDD for checkpointing. It will be saved to a file inside the checkpoint
directory set with SparkContext.setCheckpointDir() and all references to its parent
RDDs will be removed. This function must be called before any job has been
executed on this RDD. It is strongly recommended that this RDD is persisted in
memory, otherwise saving it on a file will require recomputation.

Aggregate the elements of each partition, and then the results for all the partitions, using a
given associative function and a neutral "zero value".

Aggregate the elements of each partition, and then the results for all the partitions, using a
given associative function and a neutral "zero value". The function op(t1, t2) is allowed to
modify t1 and return it as its result value to avoid object allocation; however, it should not
modify t2.

final defne(arg0: AnyRef): Boolean

final defnotify(): Unit

final defnotifyAll(): Unit

Set this RDD's storage level to persist its values across operations after the first time
it is computed.

Set this RDD's storage level to persist its values across operations after the first time
it is computed. This can only be used to assign a new storage level if the RDD does not
have a storage level set yet..

Uses this partitioner/partition size, because even if other is huge, the resulting
RDD will be <= us.

final defsynchronized[T0](arg0: ⇒ T0): T0

Definition Classes

AnyRef

deftake(num: Int): List[T]

Take the first num elements of the RDD.

Take the first num elements of the RDD. This currently scans the partitions *one by one*, so
it will be slow if a lot of partitions are required. In that case, use collect() to get the
whole RDD instead.

final defwait(arg0: Long): Unit

Zips this RDD with another one, returning key-value pairs with the first element in each RDD,
second element in each RDD, etc.

Zips this RDD with another one, returning key-value pairs with the first element in each RDD,
second element in each RDD, etc. Assumes that the two RDDs have the *same number of
partitions* and the *same number of elements in each partition* (e.g. one was made through
a map on the other).

Zip this RDD's partitions with one (or more) RDD(s) and return a new RDD by
applying a function to the zipped partitions.

Zip this RDD's partitions with one (or more) RDD(s) and return a new RDD by
applying a function to the zipped partitions. Assumes that all the RDDs have the
*same number of partitions*, but does *not* require them to have the same number
of elements in each partition.